Releases: Julia-XAI/ExplainableAI.jl
Releases · Julia-XAI/ExplainableAI.jl
v0.5.5
v0.5.4
ExplainableAI v0.5.4
Closed issues:
- Add printing of LRP analyzers, showing layers and rules (#83)
Merged pull requests:
v0.5.3
v0.5.2
ExplainableAI v0.5.2
Closed issues:
- Use CIFAR10 examples instead of MNIST (#49)
Merged pull requests:
v0.5.1
ExplainableAI v0.5.1
v0.5.0
ExplainableAI v0.5.0
Closed issues:
- Add passthrough rule (#60)
- Apply LRP rules via VJP with gradient mapper (#62)
- Refactor gradient methods to make use of VJPs (#68)
Merged pull requests:
- Replace LRP gradient computation with VJP using
Zygote.pullback
(#72) (@adrhill) - In-place modify layers and rewrite
ZBoxRule
to use VJP (#73) (@adrhill) - Fix broadcasting for Julia 1.6 (#74) (@adrhill)
- Add compatibility checks for LRP rule & layer combinations (#75) (@adrhill)
- Add
PassRule
(#76) (@adrhill) - Fix bug in
ZBoxRule
(#77) (@adrhill) - Add
AlphaBetaRule
(#78) (@adrhill)
v0.4.0
ExplainableAI v0.4.0
Closed issues:
- Reduce allocations in LRP methods (#19)
- Add Integrated Gradients analyzer (#54)
- Remove use of
mapreduce
(#55) - Simplify heatmapping normalizer using ColorSchemes
v3.18
(#56) - Specify upper and lower bounds of input in ZBoxRule constructor (#61)
Merged pull requests:
- Update heatmapping normalizer (#57) (@adrhill)
- Remove use of
mapreduce
(#58) (@adrhill) - Add Integrated Gradients analyzer (#65) (@adrhill)
- Add LoopVectorization.jl to tests and benchmarks to speed up Tullio (#66) (@adrhill)
- Run LRP rule tests on batches (#67) (@adrhill)
- Fix
ZBoxRule
(#69) (@adrhill) - Refactor
lrp!
(#70) (@adrhill)
v0.3.3
v0.3.2
ExplainableAI v0.3.2
Merged pull requests: